{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7ae19660",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Machine Learning with PyTorch and Scikit-Learn  \n",
    "# -- Code Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22959aae",
   "metadata": {},
   "source": [
    "## Package version checks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05edf0fb",
   "metadata": {},
   "source": [
    "Add folder to path in order to load from the check_packages.py script:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "73f8c3d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.insert(0, '..')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10c32840",
   "metadata": {},
   "source": [
    "Check recommended package versions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a677e37b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[OK] Your Python version is 3.8.12 | packaged by conda-forge | (default, Oct 12 2021, 21:59:51) \n",
      "[GCC 9.4.0]\n",
      "[OK] torch 1.10.1+cu102\n",
      "[OK] torchvision 0.11.2+cu102\n",
      "[OK] tensorboard 2.7.0\n",
      "[OK] pytorch_lightning 1.5.1\n",
      "[OK] torchmetrics 0.6.2\n"
     ]
    }
   ],
   "source": [
    "from python_environment_check import check_packages\n",
    "\n",
    "\n",
    "d = {\n",
    "    'torch': '1.8',\n",
    "    'torchvision': '0.9.0',\n",
    "    'tensorboard': '2.7.0',\n",
    "    'pytorch_lightning': '1.5.0',\n",
    "    'torchmetrics': '0.6.2'\n",
    "}\n",
    "check_packages(d)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a1afff8",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Chapter 13: Going Deeper -- the Mechanics of PyTorch (Part 3/3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17db22a8",
   "metadata": {},
   "source": [
    "**Outline**\n",
    "\n",
    "- [Higher-level PyTorch APIs: a short introduction to PyTorch Lightning](#Higher-level-PyTorch-APIs-a-short-introduction-to-PyTorch-Lightning)\n",
    "  - [Setting up the PyTorch Lightning model](#Setting-up-the-PyTorch-Lightning-model)\n",
    "  - [Setting up the data loaders for Lightning](#Setting-up-the-data-loaders-for-Lightning)\n",
    "  - [Training the model using the PyTorch Lightning Trainer class](#Training-the-model-using-the-PyTorch-Lightning-Trainer-class)\n",
    "  - [Evaluating the model using TensorBoard](#Evaluating-the-model-using-TensorBoard)\n",
    "- [Summary](#Summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dfd5e76",
   "metadata": {},
   "source": [
    "## Higher-level PyTorch APIs: a short introduction to PyTorch Lightning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f80b149",
   "metadata": {},
   "source": [
    "### Setting up the PyTorch Lightning model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5dcd4005",
   "metadata": {},
   "source": [
    "## Higher-level PyTorch APIs: a short introduction to PyTorch Lightning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a65b5dc",
   "metadata": {},
   "source": [
    "### Setting up the PyTorch Lightning model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "25c33c8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pytorch_lightning as pl\n",
    "import torch \n",
    "import torch.nn as nn \n",
    "\n",
    "from torchmetrics import __version__ as torchmetrics_version\n",
    "from pkg_resources import parse_version\n",
    "\n",
    "from torchmetrics import Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9c4d84a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MultiLayerPerceptron(pl.LightningModule):\n",
    "    def __init__(self, image_shape=(1, 28, 28), hidden_units=(32, 16)):\n",
    "        super().__init__()\n",
    "        \n",
    "        # new PL attributes:\n",
    "        \n",
    "        if parse_version(torchmetrics_version) > parse_version(\"0.8\"):\n",
    "            self.train_acc = Accuracy(task=\"multiclass\", num_classes=10)\n",
    "            self.valid_acc = Accuracy(task=\"multiclass\", num_classes=10)\n",
    "            self.test_acc = Accuracy(task=\"multiclass\", num_classes=10)\n",
    "        else:\n",
    "            self.train_acc = Accuracy()\n",
    "            self.valid_acc = Accuracy()\n",
    "            self.test_acc = Accuracy()\n",
    "        \n",
    "        # Model similar to previous section:\n",
    "        input_size = image_shape[0] * image_shape[1] * image_shape[2] \n",
    "        all_layers = [nn.Flatten()]\n",
    "        for hidden_unit in hidden_units: \n",
    "            layer = nn.Linear(input_size, hidden_unit) \n",
    "            all_layers.append(layer) \n",
    "            all_layers.append(nn.ReLU()) \n",
    "            input_size = hidden_unit \n",
    " \n",
    "        all_layers.append(nn.Linear(hidden_units[-1], 10)) \n",
    "        self.model = nn.Sequential(*all_layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.model(x)\n",
    "        return x\n",
    "\n",
    "    def training_step(self, batch, batch_idx):\n",
    "        x, y = batch\n",
    "        logits = self(x)\n",
    "        loss = nn.functional.cross_entropy(logits, y)\n",
    "        preds = torch.argmax(logits, dim=1)\n",
    "        self.train_acc.update(preds, y)\n",
    "        self.log(\"train_loss\", loss, prog_bar=True)\n",
    "        return loss\n",
    "\n",
    "    def training_epoch_end(self, outs):\n",
    "        self.log(\"train_acc\", self.train_acc.compute())\n",
    "        self.train_acc.reset()\n",
    "    \n",
    "    def validation_step(self, batch, batch_idx):\n",
    "        x, y = batch\n",
    "        logits = self(x)\n",
    "        loss = nn.functional.cross_entropy(logits, y)\n",
    "        preds = torch.argmax(logits, dim=1)\n",
    "        self.valid_acc.update(preds, y)\n",
    "        self.log(\"valid_loss\", loss, prog_bar=True)\n",
    "        return loss\n",
    "    \n",
    "    def validation_epoch_end(self, outs):\n",
    "        self.log(\"valid_acc\", self.valid_acc.compute(), prog_bar=True)\n",
    "        self.valid_acc.reset()\n",
    "\n",
    "    def test_step(self, batch, batch_idx):\n",
    "        x, y = batch\n",
    "        logits = self(x)\n",
    "        loss = nn.functional.cross_entropy(logits, y)\n",
    "        preds = torch.argmax(logits, dim=1)\n",
    "        self.test_acc.update(preds, y)\n",
    "        self.log(\"test_loss\", loss, prog_bar=True)\n",
    "        self.log(\"test_acc\", self.test_acc.compute(), prog_bar=True)\n",
    "        return loss\n",
    "\n",
    "    def configure_optimizers(self):\n",
    "        optimizer = torch.optim.Adam(self.parameters(), lr=0.001)\n",
    "        return optimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05077828",
   "metadata": {},
   "source": [
    "### Setting up the data loaders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d425db45",
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "from torch.utils.data import random_split\n",
    " \n",
    "from torchvision.datasets import MNIST\n",
    "from torchvision import transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15878ed0",
   "metadata": {},
   "outputs": [],
   "source": [
    "class MnistDataModule(pl.LightningDataModule):\n",
    "    def __init__(self, data_path='./'):\n",
    "        super().__init__()\n",
    "        self.data_path = data_path\n",
    "        self.transform = transforms.Compose([transforms.ToTensor()])\n",
    "        \n",
    "    def prepare_data(self):\n",
    "        MNIST(root=self.data_path, download=True) \n",
    "\n",
    "    def setup(self, stage=None):\n",
    "        # stage is either 'fit', 'validate', 'test', or 'predict'\n",
    "        # here note relevant\n",
    "        mnist_all = MNIST( \n",
    "            root=self.data_path,\n",
    "            train=True,\n",
    "            transform=self.transform,  \n",
    "            download=False\n",
    "        ) \n",
    "\n",
    "        self.train, self.val = random_split(\n",
    "            mnist_all, [55000, 5000], generator=torch.Generator().manual_seed(1)\n",
    "        )\n",
    "\n",
    "        self.test = MNIST( \n",
    "            root=self.data_path,\n",
    "            train=False,\n",
    "            transform=self.transform,  \n",
    "            download=False\n",
    "        ) \n",
    "\n",
    "    def train_dataloader(self):\n",
    "        return DataLoader(self.train, batch_size=64, num_workers=4)\n",
    "\n",
    "    def val_dataloader(self):\n",
    "        return DataLoader(self.val, batch_size=64, num_workers=4)\n",
    "\n",
    "    def test_dataloader(self):\n",
    "        return DataLoader(self.test, batch_size=64, num_workers=4)\n",
    "    \n",
    "    \n",
    "torch.manual_seed(1) \n",
    "mnist_dm = MnistDataModule()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f02630e2",
   "metadata": {},
   "source": [
    "### Training the model using the PyTorch Lightning Trainer class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0e74ca1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "2022-02-21 00:05:52.412727: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0\n",
      "\n",
      "  | Name      | Type       | Params\n",
      "-----------------------------------------\n",
      "0 | train_acc | Accuracy   | 0     \n",
      "1 | valid_acc | Accuracy   | 0     \n",
      "2 | test_acc  | Accuracy   | 0     \n",
      "3 | model     | Sequential | 25.8 K\n",
      "-----------------------------------------\n",
      "25.8 K    Trainable params\n",
      "0         Non-trainable params\n",
      "25.8 K    Total params\n",
      "0.103     Total estimated model params size (MB)\n"
     ]
    },
    {
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      "text/plain": [
       "Validation sanity check: 0it [00:00, ?it/s]"
      ]
     },
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      "text/plain": [
       "Training: 0it [00:00, ?it/s]"
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    {
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      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
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    {
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   ],
   "source": [
    "from pytorch_lightning.callbacks import ModelCheckpoint\n",
    "\n",
    "\n",
    "mnistclassifier = MultiLayerPerceptron()\n",
    "\n",
    "callbacks = [ModelCheckpoint(save_top_k=1, mode='max', monitor=\"valid_acc\")] # save top 1 model\n",
    "\n",
    "if torch.cuda.is_available(): # if you have GPUs\n",
    "    trainer = pl.Trainer(max_epochs=10, callbacks=callbacks, gpus=1)\n",
    "else:\n",
    "    trainer = pl.Trainer(max_epochs=10, callbacks=callbacks)\n",
    "\n",
    "trainer.fit(model=mnistclassifier, datamodule=mnist_dm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f57fecb",
   "metadata": {},
   "source": [
    "### Evaluating the model using TensorBoard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b58db4a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at /home/jovyan/ch13/lightning_logs/version_0/checkpoints/epoch=8-step=7739.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at /home/jovyan/ch13/lightning_logs/version_0/checkpoints/epoch=8-step=7739.ckpt\n"
     ]
    },
    {
     "data": {
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       "model_id": "f7ff6fc711ec4682a527cedb2fda48d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "DATALOADER:0 TEST RESULTS\n",
      "{'test_acc': 0.9499600529670715, 'test_loss': 0.14912301301956177}\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'test_loss': 0.14912301301956177, 'test_acc': 0.9499600529670715}]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=mnistclassifier, datamodule=mnist_dm, ckpt_path='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "19911b5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "\n",
    "\n",
    "Image(filename='figures/13_09.png') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a482c6ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "      <iframe id=\"tensorboard-frame-ee813fea1a67b712\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
       "      </iframe>\n",
       "      <script>\n",
       "        (function() {\n",
       "          const frame = document.getElementById(\"tensorboard-frame-ee813fea1a67b712\");\n",
       "          const url = new URL(\"/\", window.location);\n",
       "          const port = 6006;\n",
       "          if (port) {\n",
       "            url.port = port;\n",
       "          }\n",
       "          frame.src = url;\n",
       "        })();\n",
       "      </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start tensorboard\n",
    "%load_ext tensorboard\n",
    "%tensorboard --logdir lightning_logs/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "30675659",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='figures/13_10.png') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "53bc8027",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/checkpoint_connector.py:45: LightningDeprecationWarning: Setting `Trainer(resume_from_checkpoint=)` is deprecated in v1.5 and will be removed in v1.7. Please pass `Trainer.fit(ckpt_path=)` directly instead.\n",
      "  rank_zero_deprecation(\n",
      "Trainer already configured with model summary callbacks: [<class 'pytorch_lightning.callbacks.model_summary.ModelSummary'>]. Skipping setting a default `ModelSummary` callback.\n",
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py:1893: LightningDeprecationWarning: `trainer.resume_from_checkpoint` is deprecated in v1.5 and will be removed in v1.7. Specify the fit checkpoint path with `trainer.fit(ckpt_path=)` instead.\n",
      "  rank_zero_deprecation(\n",
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/core/datamodule.py:469: LightningDeprecationWarning: DataModule.setup has already been called, so it will not be called again. In v1.6 this behavior will change to always call DataModule.setup.\n",
      "  rank_zero_deprecation(\n",
      "Restoring states from the checkpoint path at lightning_logs/version_0/checkpoints/epoch=8-step=7739.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/checkpoint_connector.py:247: UserWarning: You're resuming from a checkpoint that ended mid-epoch. Training will start from the beginning of the next epoch. This can cause unreliable results if further training is done, consider using an end of epoch checkpoint.\n",
      "  rank_zero_warn(\n",
      "Restored all states from the checkpoint file at lightning_logs/version_0/checkpoints/epoch=8-step=7739.ckpt\n",
      "\n",
      "  | Name      | Type       | Params\n",
      "-----------------------------------------\n",
      "0 | train_acc | Accuracy   | 0     \n",
      "1 | valid_acc | Accuracy   | 0     \n",
      "2 | test_acc  | Accuracy   | 0     \n",
      "3 | model     | Sequential | 25.8 K\n",
      "-----------------------------------------\n",
      "25.8 K    Trainable params\n",
      "0         Non-trainable params\n",
      "25.8 K    Total params\n",
      "0.103     Total estimated model params size (MB)\n",
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/callbacks/model_checkpoint.py:617: UserWarning: Checkpoint directory /home/jovyan/ch13/lightning_logs/version_0/checkpoints exists and is not empty.\n",
      "  rank_zero_warn(f\"Checkpoint directory {dirpath} exists and is not empty.\")\n"
     ]
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      },
      "text/plain": [
       "Validating: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/conda/lib/python3.8/site-packages/pytorch_lightning/core/datamodule.py:469: LightningDeprecationWarning: DataModule.teardown has already been called, so it will not be called again. In v1.6 this behavior will change to always call DataModule.teardown.\n",
      "  rank_zero_deprecation(\n"
     ]
    }
   ],
   "source": [
    "path = 'lightning_logs/version_0/checkpoints/epoch=8-step=7739.ckpt'\n",
    "\n",
    "if torch.cuda.is_available(): # if you have GPUs\n",
    "    trainer = pl.Trainer(\n",
    "        max_epochs=15, callbacks=callbacks, resume_from_checkpoint=path, gpus=1\n",
    "    )\n",
    "else:\n",
    "    trainer = pl.Trainer(\n",
    "        max_epochs=15, callbacks=callbacks, resume_from_checkpoint=path\n",
    "    )\n",
    "\n",
    "trainer.fit(model=mnistclassifier, datamodule=mnist_dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5100164a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='figures/13_11.png') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6250f819",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Reusing TensorBoard on port 6006 (pid 702), started 0:02:27 ago. (Use '!kill 702' to kill it.)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "      <iframe id=\"tensorboard-frame-aeb0045bdadd4303\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
       "      </iframe>\n",
       "      <script>\n",
       "        (function() {\n",
       "          const frame = document.getElementById(\"tensorboard-frame-aeb0045bdadd4303\");\n",
       "          const url = new URL(\"/\", window.location);\n",
       "          const port = 6006;\n",
       "          if (port) {\n",
       "            url.port = port;\n",
       "          }\n",
       "          frame.src = url;\n",
       "        })();\n",
       "      </script>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%tensorboard --logdir lightning_logs/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6649887c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f401041e7f834630b51700fe61486e30",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "DATALOADER:0 TEST RESULTS\n",
      "{'test_acc': 0.9542893767356873, 'test_loss': 0.14718961715698242}\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'test_loss': 0.14718961715698242, 'test_acc': 0.9542893767356873}]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=mnistclassifier, datamodule=mnist_dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7e828950",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at /home/jovyan/ch13/lightning_logs/version_0/checkpoints/epoch=13-step=12039.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at /home/jovyan/ch13/lightning_logs/version_0/checkpoints/epoch=13-step=12039.ckpt\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8db54d5842b54b9686aeecbc4b4d30fb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "DATALOADER:0 TEST RESULTS\n",
      "{'test_acc': 0.9559454321861267, 'test_loss': 0.14512717723846436}\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[{'test_loss': 0.14512717723846436, 'test_acc': 0.9559454321861267}]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=mnistclassifier, datamodule=mnist_dm, ckpt_path='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cb35f015",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"lightning_logs/version_0/checkpoints/epoch=13-step=12039.ckpt\"\n",
    "model = MultiLayerPerceptron.load_from_checkpoint(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "115eda85",
   "metadata": {},
   "source": [
    "## Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "052a0344",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Readers may ignore the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "844a218f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook ch13_part3_lightning.ipynb to script\n",
      "[NbConvertApp] Writing 7321 bytes to ch13_part3_lightning.py\n"
     ]
    }
   ],
   "source": [
    "! python ../.convert_notebook_to_script.py --input ch13_part3_lightning.ipynb --output ch13_part3_lightning.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7417724",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
